parsingNDArray：解析 MXNet 参数文件并提取预训练参数的工具（C++）

Parsing MXNet Parameter File In C++

This small project aims to extract parameters from pretrained MXNet .params file in C++, and only depends on the dmlc-core project.

If you want to run your MXNet pretrained model on mobile devices with other light weight frameworks, for example ncnn . You need to first extract the pretrained parameters from the .params file.

This project provides you the facility to parse the .params file and extract the weights in C++.

Build The Project

mkdir build && cd build && cmake .. && make -j

Testing

The test.py script constructs a simple nerwork with only 2 fc layers.

import mxnet as mx

data = mx.sym.Variable('data')
fc = mx.sym.FullyConnected(data=data, num_hidden=100, no_bias=False, name='fc1')
fc = mx.sym.FullyConnected(data=fc, num_hidden=1, no_bias=False, name='fc2')

And it will generate a .params file contains random init weights by running the script.

cd testData && python test.py

Then you can load the .params file and perform forward operation in C++.

cd build && ./read_nd

And the forward result will be the same as the output of python script.

Some Limitations & Future Works

1. This tool has only been tested on the lastest MXNet version V 1.2.0, which may not work with older MXNet version.
2. I have only implemented the parsing of normal storage type NDArray, if your .params file contains sparse NDArray, this tool will fail to parse the file.
3. For now this project has to depend on the dmlc-core project, which I want to remove the dependency in the future improvement.